Long-distance movements of harbour seals (<i>Phoca vitulina</i>) from a seasonally ice-covered area, the St. Lawrence River estuary, Canada
Bibliographic record
Abstract
Previous studies of harbour seal (Phoca vitulina L., 1758) movements indicate that this species is relatively sedentary throughout the year. However, few investigations have examined their movements and seasonal distribution patterns in ice-covered areas. This study used spatial analysis of ice data and movement data from harbour seals collected via satellite (n = 7) and VHF radiotelemetry (n = 15) to explore this species' spatial use patterns in a seasonally ice-covered region, the St. Lawrence River estuary, Canada. When solid ice formed within the bays of the estuary, four of the seven satellite-tagged animals (all adult males) left their summer haul-out areas, migrating 266 ± 202 km (range 65–520 km) to over-wintering sites. The seals exhibited preference for areas of light to intermediate ice conditions during the winter months; at least six of the seven seals occupied areas with lighter ice conditions than those that prevailed generally in the study area. Evidence of high abundance of potential prey for harbour seals in the estuary during winter suggests that reduced availability of adequate food resources is not the primary factor which influences the movement and distribution patterns of harbour seals. Movement patterns observed during the ice-free period concur with previously reported harbour seal behaviour; the seals remained near the coast (<6.1–11.0 km from shore) in shallow water areas (<50 m deep in 100% VHF and 90% SLTDRs (satellite-linked time-depth recorders)) and travelled only short distances (15–45 km) from capture sites. None of the VHF- or satellite-tagged seals crossed the 350 m deep Laurentian channel, which suggests that this deep body of water might represent a physical barrier to this coastal population.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".